1

Title: Mesophyll diffusion conductance to CO2: an unappreciated central player in photosynthesis

Authors: Jaume Flexas1*, Margaret M. Barbour2, Oliver Brendel3, H. M. Cabrera1,4, Marc

Carriquí1, Antonio Diaz-Espejo5, Cyril Douthe3,9, Erwin Dreyer3, Juan P. Ferrio JP6, Alexander

Galle1, Jeroni Galmés1, Naomi Kodama7, Hipolito Medrano1, Ülo Niinemets8, Jose J. Peguero-

Pina1, Alicia Pou1, Miquel Ribas-Carbo1, Magdalena Tomas1, Tiina Tosens8, Charles R. Warren9

1. Research Group in Plant Biology under Mediterranean Conditions, Universitat de les Illes Balears; Carretera de

Valldemossa Km 7.5; 07122 Palma de Mallorca, Illes Balears, Spain

2. Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Private Bag 4011, Narellan NSW

2567, Australia

3. INRA, UMR 1137 “Ecologie et Ecophysiologie Forestières”, F 54280 Champenoux

3. Université de Lorraine, UMR 1137 “Ecologie et Ecophysiologie Forestières”, Faculté des Sciences, F54500

Vandoeuvre, France

4. Centro de Ecología Aplicada Ltda., Av. Suecia 3304, Ñuñoa, Santiago, Chile

5. Instituto de Recursos Naturales y Agrobiología, IRNAS-CSIC, Apartado 1052, 41080, Sevilla, Spain

6. Department of Crop and Forest Sciences, ETSEA, Universitat de Lleida, Avda. Rovira Roure 191; 25198 Lleida,

Spain

7. Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, 3-1-3 Kannondai, Tsukuba, 305-

8604 Japan

8. Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, Kreutzwaldi 1, Tartu

51014, Estonia

9. School of Biological Sciences, The University of Sydney, NSW 2006, Australia

*Corresponding author: Jaume Flexas

e-mail jaume.flexas@uib.es / fax 34 / 971 / 173184 / tel 34 / 971 / 172365

Grup de Recerca en Biologia de les Plantes en Condicions Mediterrànies, Departament de

Biologia, Universitat de les Illes Balears. Carretera de Valldemossa Km 7.5, 07122 Palma de

Mallorca, Balears, SPAIN.

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Keywords

aquaporins, climate change, conductance, diffusion, leaf anatomy, plant hydraulics, photosynthesis

Table of contents

Abstract

1. Introduction

2. How different is gm among phylogenetically distant groups and how has gm evolved?

3. New evidence as for the main determinants of gm

3.1. Changing the nature of the diffusing molecule: carbonic anhydrases

3.2. Changing the nature of the diffusing medium: aquaporins

3.3. Changing the diffusing distance: anatomical properties of leaves and cells

4. Which environmental conditions does gm respond to?

4.1. Acclimation to and recovery after drought and salinity

4.2. Nutrient stress

4.3. Changing CO2 concentration around leaves

5. How important is gm in limiting photosynthesis?

5.1. Photosynthesis limitations in response to environmental variables

5.2. Photosynthesis limitations within complex canopies

6. Modeling and including gm in photosynthesis models

7. Can gm be uncoupled from the water path regulation?

7.1. Co-regulation of gm and stomatal conductance

7.2. Co-regulation of gm and hydraulic conductance in the mesophyll

8. Concluding remarks and future prospects

Acknowledgements

References

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Abstract

Mesophyll diffusion conductance CO2 is a key photosynthetic trait that has been studied

intensively in the past years. The intention of the present review is to update the knowledge on gm,

and highlight the important unknown and controversial aspects that require future work. The

photosynthetic limitation imposed by mesophyll conductance is large, and under certain conditions

it can be the most significant photosynthetic limitation. New evidence shows that anatomical traits,

such as cell wall thickness and chloroplast distribution are amongst the stronger determinants of

mesophyll conductance, although rapid variations in response to environmental changes might be

regulated by other factors such as aquaporin conductance.

There are a number of gaps in knowledge that should be major research priorities for the

near future include, how different is mesophyll conductance among phylogenetically distant

groups and how has it evolved? can it be uncoupled from the water path regulation? what are the

main drivers of mesophyll conductance? The need for mechanistic and phenomenological models

of mesophyll conductance and its incorporation in process-based photosynthesis models is also

highlighted.

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1. Introduction

Photosynthesis in plants has been considered for decades to be limited only by two factors:

the velocity of diffusion of CO2 through stomata and the capacity of photosynthetic machinery in

leaves to convert light energy to biochemical energy and fix CO2 into sugars. While diffusion is a

passive physical process, it can be subject to large regulation in plants. According to Fick's law,

diffusion depends on substance (e.g. CO2) diffusivity, which differs depending on temperature but

also on the nature (mainly viscosity) of the media in which diffusion occurs (e.g. water, air, etc.),

and the distance of diffusion. Since the mesophyll pathway consists of a complex array of

‘physical barriers’ to CO2 diffusion, including air, cell walls, lipid membranes and liquid

cytoplasm and stroma, differing both in nature and size (i.e. 'distance'), there is a large variation

among leaves in diffusion conductance to CO2 in the mesophyll (gm), and the latter can be

regulated by changing either the distance or the nature of (part of) the diffusion pathway inside

leaves.

Early studies already suggested that the diffusion of CO2 from sub-stomatal cavities to the sites of

carboxylation inside chloroplasts could limit photosynthesis (e.g., [1-3]), which has become more

evident after several methods for the estimation of gm have become more available – including a

method based on 13C-discrimination during photosynthesis[4], a method combining chlorophyll

fluorescence and gas exchange measurements [5, 6] and model-based methods [6-8]. For details on

methods for gm estimation, the required precautions when using them and specific strategies of

adjustment, see refs [9], [10], [11]. Thus, although during decades the majority of researchers

considered gm large enough not to significantly limit photosynthesis, it has become now evident

that that gm is the third major player in the process of photosynthesis, together with stomatal

conductance and biochemical capacity.

The current understanding on gm has been recently reviewed [12]. In addition, specific

reviews on the mechanisms regulating gm [13], and on the ecophysiological and ecological

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significance of gm [14-16] have been published. These papers are recommended as the best

introduction to the importance of gm in plant physiology. As there has been rapid gain in

understanding of gm, the aims of the present paper are: (1) to update information of current

knowledge accumulated after the recent reviews; (2) to discuss the most obscure / controversial

aspects on gm function and regulation, such as its response to CO2, or how much it limits

photosynthesis; and (3) to highlight the obvious gaps in knowledge on this subject and the future

research needs.

2. How different is gm among phylogenetically distant groups and how have

mechanisms controlling gm evolved?

The rate of diffusion conductance to CO2 in the mesophyll (gm) has now been estimated for

more than 100 species, and it is now possible to search for phylogenetic / evolutionary patterns.

The vast majority of estimates of gm are for Spermatophytes [14] (angiosperms and

gymnosperms), with only very few data for liverworts and hornworts [17]. Most surprisingly there

are no measurements available for phylogenetically intermediate groups such as mosses,

lycophytes, equisetophytes, or ferns. This constitutes a serious gap in our knowledge that

precludes driving any broad conclusion as for the evolution of mechanisms controlling gm.

Some valuable information can nevertheless be obtained by comparing the existing data for

liverworts and hornwort gametophytes with those for Spermatophytes belonging to different

phylogenetic and/or functional groups (Fig.1). At first sight, it is evident that there are variations in

the average rate of gm among different plant groups, and that these variations are more closely

correlated with evolutionary advancements than stomatal conductance (gs). The largest values for

both conductances are found among non-woody angiosperms, whereas grasses present somewhat

higher gm values than annual dicots (Fig. 1). The lowest values are found in liverworts and

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hornworts for which gs is set as zero as they lack stomata, and CO2 has to diffuse through the

cuticle and epidermis. Among Spermatophytes, conifers show the lowest values. Since

angiosperms are evolutionary more recent than gymnosperms and non-Spermatophytes (the

earliest fossil records for conifers dating back to 290 Myr as compared to 200 Myr for

angiosperms) and grasses represent a relatively recent evolutionary event (ca. 70 Myr), an

evolutionary trend towards larger gm than gs values is plausible. Accordingly, gas exchange

capacity of Angiosperms was greatly increased following the Cretaceous period in association

with leaf morphological changes [18].

A closer inspection reveals that significant differences also appear among angiosperms as a

function of their functional type or growth form. Hence, herbaceous plants show the highest

values, followed by semi-deciduous and deciduous shrubs and trees, while the lowest values are

found in evergreen shrubs and trees, similar to those displayed by gymnosperms. Therefore, at

least, part of the observed variation may not reflect evolutionary trends but is simply the result of

adaptations to particular growth forms and/or environments, e.g., thicker leaves having lower gm

(see next section). Conversely, in some of the groups displayed in Fig. 1, the number of species

included is low and biased. For instance, there are only three genera within grasses (monocots) for

which gm has been determined (Triticum, Oryza and Phragmites), while herbaceous genera are

dicots. Hence, currently available data do not allow distinguishing patterns between monocots and

dicots, or separating the effects of life form and phylogenetic position.

In the case of hornworts and liverworts, estimates of gm are five orders of magnitude

smaller than for Spermatophytes (Fig. 1 inset). Despite the fact that hornworts and liverworts lack

stomata and show a low degree of cuticularization, they may contain some kind of cuticle or

procuticle whose conductance could affect gm estimates. However, the conductance to CO2 of the

thicker and more developed cuticle of higher plants is already around 2.5 10-4 mol m-2 s-1 [19], i.e.,

still an order of magnitude larger than gm estimated in Bryophytes [17]. This evidence suggests

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that hornworts and liverworts present a truly restricted gm, which may explain their slow growth.

Again, this strongly suggests the occurrence of an evolutionary trend towards higher gm, although

knowledge of gm values of intermediate groups – i.e. mosses and ferns – may be necessary to

confirm such a trend. It is remarkable that values found for bryophytes are similar to the lowest

values of CO2 permeabilities reported for biological membranes [13]. It is not known whether this

means that internal CO2 diffusion in tissues of early land plant forms depends on simple diffusion

through membranes without facilitating agents such as aquaporins. Of the genes encoding for

proteins possibly facilitating gm in higher plants (see section 3), no aquaporin (searched as putative

PIP1 family - i.e. Plasma membrane Integral Protein - gene) or carbonic anhydrase has been

described for hornworts, liverworts, lycophytes, equisetophytes or ferns, and only two putative

genes for PIP1 but up to 13 for carbonic anhydrase have been described in mosses

(www.ncbi.nlm.nih.gov/genbank/). However, this does not necessarily mean that these

genes/proteins do not exist is these groups, as very few data are available in databases for the

genome sequences of these species groups. Moreover, in these groups the importance of carbon

concentrating mechanisms involving carbonic anhydrases, pyrenoids, carboxysomes, etc. probably

mask the importance of gm -related components.

In summary, there is a significant gap in knowledge concerning phylogenetic/evolutionary

trends in gm. To overcome this gap it may be necessary to compile data for monocot species of

families other than Poaceae as well as for lower forms such as lycophytes, equisetophytes, ferns

and mosses. These data should be measured under the same environmental and developmental

conditions to derive phylogenetic implications from a trait like gm, which is under strong

environmental control. This knowledge will help understanding the evolution of gm, the

mechanisms involved and the extent of co-variation of gm and gs.

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3. New evidence as for the main determinants of gm

3.1. Changing the nature of the diffusing molecule: carbonic anhydrases

CO2 molecules passing from sub-stomatal cavities to chloroplasts diffuse through gas-

phase in leaf intercellular air spaces, liquid phase in cell walls, cytosol and chloroplast stroma and

lipid phase in plasmalemma and chloroplast envelope membranes (Fig. 2). The rate of diffusion

through the composite segments of the diffusion pathway depends on the effective thickness and

diffusivity of each component section [16]. “Effective” denotes the circumstance that the diffusion

path length is generally longer than the linear distance from sub-stomatal cavities to chloroplast

due to tortuosity and/or limited porosity of the diffusion pathway [20]. Diffusion coefficients for

CO2 in free water, tabulated in physical chemistry handbooks cannot be directly applied to leaves

due to presence of solutes and macromolecules in liquid-phase components of the diffusion

pathway, changes in pH, temperature, etc. [20]. Moreover, CO2 can interconvert with HCO3- inside

leaf cells in a reversible reaction catalyzed by carbonic anhydrases. Since the diffusivities of CO2

and HCO3- as well as their pH and temperature dependencies differ [21] carbonic anhydrases could

play a role on the regulation of gm by means of changing the nature of the diffusing molecule.

Early work [22, 23] showed that extremely high reduction in carbonic anhydrase activity

did not result in major photosynthetic limitation. However, it has been also shown that the

contribution of carbonic anhydrase to gm is species dependent, and their role may become more

important when gm is low as in sclerophyllous species [24]. Moreover many different carbonic

anhydrases, with different cellular locations have been characterized [25] and it has been

suggested that carbonic anhydrases can account of 1% of total protein, and those located in

chloroplasts (βCA1 and βCA5) could potentially contribute to increase gm. Up to now, however,

genetic modification of different forms of carbonic anhydrases in Arabidopsis, either chloroplastic

or not, have resulted in differently phenotypes differing in growth but with no measurable

difference in gm (Genty, personal communication). Despite of these results, a role of carbonic

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anhydrases in the regulation of gm in some species and/or under certain conditions cannot be ruled

out.

3.2. Changing the nature of the diffusing medium: aquaporins

Besides the nature of the diffusing molecule (i.e., CO2 or HCO3-), carbon dioxide diffusion can be

altered either by the nature or the distance of the diffusion media. Concerning the nature of the

diffusion media, the lipid phase is presumably more limiting for CO2 diffusion than the aqueous

phase and this in turn more limiting than the air phase. Membranes (cell, chloroplast) constitute the

physical components of the lipid phase. Although the rate of diffusion of CO2 through membranes

has been often considered very large and the lipid phase assumed to have a negligible effect on

CO2 diffusion, there is still a debate over the degree to which biological membranes are permeable

to CO2, and estimated permeation coefficients vary over several orders of magnitude [26-28]. With

the discovery of aquaporins, it has been suggested that apart from their function in facilitating

water diffusion across membranes they constitute a key means for regulating CO2 diffusion

through membranes [29-31]. Altered expression of aquaporins has been shown to result in changes

in membrane permeability to CO2 in plants [32, 33] and in animals [30, 34]. Experimental

evidence in favor of an important role for aquaporins in CO2 diffusion in intact leaves comes from

studies demonstrating enhanced photosynthesis in plants over-expressing aquaporins, and reduced

photosynthesis in genetically modified plants with impaired aquaporin function (Fig. 3). These

changes are driven at least in part by changes in gm [32-36]. Similarly, reduced photosynthesis and

gm are observed in plants in which aquaporins have been inhibited by HgCl2 [37-39]. However,

genetic transformation to change aquaporin expression and HgCl2 inhibition also lead to

simultaneous changes in net CO2 assimilation rates (An) and stomatal conductance (gs) (Fig. 3, 4)

[40]. Indeed, the relative diffusion limitation of photosynthesis due to gm is directly related to the

CO2 drawdown from sub-stomatal cavities to chloroplasts (Ci-Cc = An/gm) that depends on gm, An

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and gs (Ci = f(An, gs)) [41, 42]. Therefore, demonstrating changes in gm is not sufficient to confirm

an alteration in the degree to which mesophyll diffusion limits photosynthesis.

Inherent limitation of drawing broad conclusions from such studies is the lack of biological

replication, even if multiple transformed lines have been used in specific studies. So far, no study

with transformants has looked into the changes in quantitative limitations between biochemistry,

stomata and mesophyll diffusion. We calculated the limitations of photosynthesis due to stomata

(ls), mesophyll diffusion conductance (lm) and biochemistry (lb) according to Grassi and

Magnani[43]:

( )

( )

kg

gl

kgg

kgl

kgg

kgl

+=

+=

+=

tot

totb

totm

totm

tots,CO2

tots

(1)

where gs,CO2 is the stomatal conductance to CO2, gtot is the total diffusion conductance for CO2

determined as:

ms,CO2

tot 111

gg

g+

= , (2)

and k is the first derivative of net assimilation rate An with respect to chloroplastic CO2 and is

given as [44]:

( )( )2

mc

mcmax *

KC

KVk

++Γ= , (3)

where Vcmax is the maximum carboxylase activity of Rubisco, Γ*is the hypothetical CO2

compensation point in the absence of dark respiration, and Km is the effective Michaelis-Menten

constant for CO2 that considers the competitive inhibition by O2. Rubisco kinetic characteristics

were taken from Niinemets and Tenhunen [45] and Cc was the value reported in the given study.

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Due to lack of biological replication, we had to pool different aquaporins atpip1;2-1,

atpip2;3-1, Nt AQP1, HvPIP2;1 in the quantitative limitation analysis. Nevertheless, the analysis

with pooled data for photosynthesis, stomatal conductance and mesophyll conductance broadly

agreed with individual published studies, i.e., that overexpressed lines generally had higher values

of these traits, while antisense transformants had lower values (Fig. 3). Analysis of the quantitative

limitations further demonstrated that the degree of gm-limitation of photosynthesis is larger in

plants with genetically reduced aquaporin levels (Fig. 3). However, in modified lines with over-

expressed aquaporins, gm limited photosynthesis to a similar degree as in control plants due to the

parallel occurrence of reduced stomatal limitation (Fig. 3). In addition, genetic modifications in

aquaporins also led to alterations in the degree of the limitation by photosynthetic capacity per se

(Fig. 3) and also can lead to changes in foliage anatomy and photosynthesis [32-36].

Therefore, there is evidence for the involvement of aquaporins in limiting photosynthetic

CO2 assimilation rate, but it is unclear whether this role is only due to their influence on gm. As for

the thermodynamics of their involvement in gm, simulations based on molecular models have

further indicated high activation energy for CO2 passage through aquaporin monomers, suggesting

that CO2 movement through aquaporins is energetically unfavorable compared with passive

diffusion through membranes, except for highly polar membranes with low CO2 solubility [46-48].

However, the aquaporin family contains a large number of homologs [49, 50], and molecular

simulation studies indicate that the energetic barrier against CO2 movement can be lowered by

only a few point mutations [47, 48], suggesting that in principle, aquaporins most probably exist

with widely varying permeability for dissolved gases. Arabidopsis aquaporin AtPIP1;2-1 has a

much higher permeability for CO2 than AtPIP2;3-1 [32], supporting this concept. It is possible that

having different aquaporins with different activation energies allows plants to regulate CO2

diffusivity and H2O diffusivity more or less independently, although water and CO2 conductances

are often co-regulated (see Section 7). In addition, aquaporin tetramers rather than monomers may

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be functionally active in CO2 conductance in tobacco [51]. This suggestion is also corroborated by

molecular simulations suggesting that the central cavity of the tetramer requires almost 50% less

activation energy for facilitating CO2 diffusion than the aquaporin monomer [48]. However, this

barrier is still relatively large compared with direct diffusion through some highly hydrophobic

membranes [48], although the theoretical physical parameters of a lipid bilayer are not necessarily

equal to those of a biological membrane [52]. It is also important to consider that all studies on

aquaporins have been conducted in herbaceous species with mesophytic leaves that have

intrinsically high gm due to thin cell walls and high surfaces of chloroplasts exposed to

intercellular air species [14, 15]. In such species, the relative contribution of lipid phase

conductance to total diffusion conductance is expected to be larger than in species with thick cell

walls and low surfaces of chloroplasts exposed such as trees, in particular evergreen trees (Fig. 2).

The bulk of diffusion conductance in evergreens is expected to be in the liquid phase, for which

the diffusion distance can be largely variable.

3.3. Changing the diffusing distance: anatomical properties of leaves and cells

The diffusion distance is given by the size of the different anatomical components of the diffusion

path. In early studies, leaf anatomical characteristics were considered to constitute the chief

limitation of gm [1, 53-57], and anatomical traits were used to infer gm [54, 56]. At the time of

these early studies, the methods to estimate gm had not yet been established, and a separation of

physical diffusion conductance (known as gm today) and biochemical conductance, a variable

quantifying the photosynthetic capacity (chiefly the carboxylase activity of Rubisco) under a

conductance formalism, could not be reliably achieved. On the basis of anatomical measurements,

it was concluded that the physical diffusion conductance inside the leaves was large compared

with the stomatal and biochemical conductances [56, 58]. However, these early studies did not

precisely characterize the thickness of cell walls and cytosol. In addition, they assumed that the

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diffusion flux in aqueous and lipid phases varies with the ratio of exposed mesophyll area (Smes) to

total leaf area (S) ratio (Smes/S) that characterizes the number of parallel diffusion pathways [54,

55]. This assumes that the exposed surface of mesophyll cells is covered by chloroplasts. Yet,

recent studies have shown that the surface of exposed chloroplasts (Sc) to leaf area ratio (Sc/S) is

generally smaller than Smes/S [15, 59-61], implying that the use of Smes/S as a substitute of Sc/S

underestimates the anatomical constraints on diffusion.

So far, strong negative correlations between gm and cell wall thickness have been demonstrated,

especially when differences in Sc/S are considered by calculating gm per unit exposed chloroplast

surface area [16]. However, there have been surprisingly few quantitative analyses linking gm to

leaf anatomy. The few studies available demonstrate that gm can be quantitatively estimated from

leaf anatomical measurements, although certain assumptions on the tortuosity of diffusion path

length in gas phase, porosity of cell wall, effective diffusion coefficient in cytosol and chloroplast

and permeability of plasmalemma and chloroplast envelope are needed [15, 62]. These

quantitative analyses have corroborated the correlative findings of the role of cell wall thickness

and Sc/S as the main determinants of gm across species with widely varying anatomy [16]. Linking

gm to detailed anatomical measurements is promising, but tedious. Conversely, gm has also been

correlated with integrated leaf traits such as leaf dry mass per unit area, thickness and density [12,

14, 63]. Although strong relationships have been observed when pooling data from multiple

studies, especially for non-stressed plants [14], significant outliers such as Australian sclerophylls

have been denoted in other studies, reflecting the circumstance that high dry mass per unit leaf

area, thickness and density are not always associated with thick cell walls [63, 64]. The

correlations between dry mass per unit leaf area and gm can also vary across environmental

gradients in water availability, that can alter cell wall thickness [15], and in light availability that

can alter Sc/S [59, 65] at given values of leaf traits such as dry mass per unit area, thickness and

density.

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4. Which environmental conditions does gm respond to?

Mesophyll conductance to CO2 responds to environmental factors either in the long term or

rapidly, i.e. in minutes-hours [10]. Recent reviews have already highlighted the incidence of

varying environmental conditions such as soil water availability, salinity, growth irradiance and

temperature on gm [12, 14]. In the recent years, the important contribution of gm in limiting

photosynthesis during drought and salinity has been emphasized, knowledge has improved as for

nutrient stress effects on gm, and many more data have been obtained regarding the controversial

effects of rapid changes in CO2 concentration on gm.

4.1. Acclimation to and recovery after drought and salinity

Under drought and salinity, the degree of photosynthesis limitation by gs and gm is similar

(see Section 5), but gm can respond to water deficit and subsequent re-watering at different

velocities than gs [66-69]. Most remarkably, gm acclimates and recovers during prolonged drought

in tobacco and grapevine plants [66, 67], while in stressed soybeans it was hardly affected [70]

despite a significant reduction of gs in all cases. In a study on tobacco [67], gm and gs first

decreased during the onset of drought, whereas during sustained drought, gm recovered to control

values despite maintenance of low gs. Moreover, drought interacted with environmental

conditions, since gm did not decrease when the experiment was repeated at lower light intensities

and milder temperatures [59]. Thus, gm does not necessarily respond in the same manner as gs

when stress is prolonged and factors other than hydraulics or water status impact on gm.

Furthermore, gm exceeded control levels after re-watering in the Mediterranean semi-deciduous

shrub Cistus albidus [71]. In C. albidus, consecutive drought and re-watering cycles resulted in a

drought cycle-dependent adjustment of leaf gas exchange towards reduced limitation by gm and

enhanced water use efficiency with each consecutive cycle, while the evergreen oak Quercus ilex

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had a very stable response during successive cycles, lowering gm and gs in parallel [71].

Acclimation of gm during prolonged drought and facilitated recovery after re-watering represent an

effective way of optimizing CO2 diffusion transiently under limited CO2 supply, thereby boosting

photosynthetic activity and water use efficiency after relief of stress. On the other hand, gm and

photosynthetic activity can vary among ecotypes of the same species under similar water

availability due to differences in e.g. photosynthetic capacity, osmotic adjustment and leaf

structure [69, 72]. Thus, plant growth form alone cannot explain the differences in gm response to

limited water availability, but may allow for contrasting general trends in photosynthesis among

evergreens and deciduous species [73]. Whole plant structure also affects leaf diffusion

components and hence the capacity to recover from and survive drought, as observed in pre-

conditioned nursery plants of different age and size [74] and in the woody legume Prosopis

velutina [75]. Low root to shoot ratios [74] as well as lasting effects of hydraulic failure [75]

resulted in a delayed or only partial recovery of gm and leaf gas exchange after re-watering.

4.2. Nutrient stress

Compared with responses to drought, little is known about the influence of plant nutrition

on gm, and only recently have the effects of nutrition been addressed. In line with some earlier

reports, leaf nitrogen content correlates positively with photosynthetic activity and gm across

several woody and herbaceous species [76-78], whereas a negative relationship of leaf nitrogen

and gm was observed when related to tree height in Pinus densiflora [79, 80]. Such a decline of gm

with tree height can be related to decreasing water potential affecting leaf expansion and structure

[80, 81].

Photosynthetic activity and gm correlated well with the supply of K in hickory seedlings

[82], whereas biochemical modifications and/or structural changes seemed to primarily limit

photosynthesis. More research is needed to gain further insight into the K - gm relationship.

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Changes in P nutrition revealed no direct effect on gm [69, 83]. Excess of Zn in Beta vulgaris and

excess nickel Ni in Populus nigra strongly decreased leaf conductance (gm and gs) [84, 85]. This

was presumably caused by changes in mesophyll structure, which affected leaves developing

during stress more than mature ones [85]. Therefore, photosynthetic activity under excess Zn and

Ni was primarily limited through impaired leaf conductance.

4.3. Changing CO2 concentration around leaves

The effects of varying CO2 concentrations on gm display different trends for long-term

(acclimation) and for short term responses. No general trend has been observed for plants grown

under elevated CO2 (i.e. 500-600 ppm) with no change, decreased or increased gm being reported,

possibly depending on the species and time [86, 87]. In contrast, changes in gm under short-term

exposure to different CO2 concentrations seem to follow a general trend across many species [88-

94], with a negative correlation between gm and sub-stomatal and/or ambient CO2 concentration

(Fig. 5). However, some exceptions have been published [95], leading to a controversy as to

whether the observed responses are real or a simple measurement artefact. The data recorded under

low CO2 (< 100 ppm) have to be taken with caution due to errors with the available techniques

[10, 89] and it seems very likely that gm declines with rising CO2 levels. The same trend was

observed with very different techniques, each relying on very different assumptions [see e.g. 9]

[11] [86] [96] [97]. As a general pattern, gm largely differs at the ends of a Ci gradient (0 to 2000

µmol mol-1) (Fig. 5). Still, variation of gm within a smaller range of CO2 concentrations might be

small. This is particularly true when referring to CO2 changes projected for the next few decades

(e.g., the range from 300 to 800 µmol mol-1 in Fig. 5, which reflects a range of ambient CO2

concentrations of about 500 to 1000 µmol mol-1).

Several explanations for the decline of gm with increasing CO2 have been proposed,

including fine adjustments for balancing Ci and Cc, and avoiding large decreases of cell pH [12]

17

and increased cell leakiness under high pCO2 [98]. However, these adjustments might be restricted

by structural conditions at the mesophyll/chloroplast level, allowing gm to change within a

relatively narrow range (see Section 3 on the possible limit of the contribution of aquaporins to

gm). Moreover, other internal factors such as respiration may also affect the determination of gm

under varying CO2 concentrations, e.g. if a constant value is assumed. The true rate varies with

CO2, but activities of respiratory pathways can change the resistance of the diffusion pathway, e.g.

by altering the mean path length [98]. In fact several reports, either theoretical [98] or empirical

[92, 99], but not others (Flexas), have described an effect of O2 concentration on gm and its

dependency on CO2 concentration. The reasons for this effect remain unclear, although the

influence of photorespiration and of changes in the spatial distribution of CO2 emission (in

mitochondria) and carboxylation (in the chloroplasts) have been claimed. Clearly, more detailed

studies are required to fully understand the effect of O2 concentration on gm.

5. How important is gm in limiting photosynthesis?

5.1. Photosynthesis limitations in response to environmental variables

Once it was demonstrated and accepted by most of the scientific community that gm is finite, and

possibly dynamically regulated, it became important to quantify how much mesophyll diffusion

limits photosynthesis. In the 90’s and beginning of this century, photosynthesis limitation by gm

was ignored - for simplicity and because of the difficulty to estimate gm with methods available -

despite the early warnings that gm was finite, variable and limiting photosynthesis ([3] [100]).

Recently, a comprehensive analysis was described where total photosynthesis limitations were

estimated and disentangled into its three components: stomatal, mesophyll and biochemical

limitation [43]. This is a relative analysis because the percentage of reduction of the net

assimilation rate for each limiting component is estimated on the basis of a control value without

any of these limitations. As the severity of the stress progresses total limitation increases and so

18

potentially does each of the three components. Up to now, such analysis has been applied mainly

to quantify water stress-induced limitations in herbaceous [90, 101] and woody species [102-105],

as well as during recovery from water stress [67, 71, 101]. The limitation of photosynthesis by gm

was followed as well during seasonal changes [106, 107], leaf ontogeny [81, 90, 108], temperature

acclimation [109], Zn contamination [84] and nitrogen and phosphorus fertilization [83]. Data for

limitation analysis from all these studies are pooled in Figure 6, in which the Total limitation was

considered 0 for the ‘control’ plants (i.e., non stress conditions), and increasingly higher for

stressed plants up to a maximum of 1. It can be observed that, as total limitation increases with

increasing stress, stomatal mesophyll conductance and, to a lesser extend, biochemical limitations

increase (Fig. 6). The scattered results are a consequence of including a number of species with

different growth forms with a range of structural and anatomical characteristics, different types of

stress, and varying severities of the same type of stress from mild to severe stress in the same

analysis. Yet, it can be observed that up to a total limitation of 25%, limitations are mainly

represented by stomata and mesophyll. From this point to larger total limitation, all three

limitations increase, but the relative contribution of stomata becomes generally the larger,

followed by that of mesophyll and, finally biochemical limitations. Cases in which mesophyll

limitations account for more than 75% of TL are under mild water stress [101], first stages of re-

watering [101], where atmospheric demand was impaired from soil water availability [105], or in

the response of photosynthesis to temperature [109]. All the data available point out that

mesophyll conductance limitations to photosynthesis are of similar magnitude as stomatal

limitations, and generally greater than biochemical limitations. Besides limiting photosynthesis in

response to environmental clues, the spatial variability of gm within canopies, especially in relation

to height in tall trees, has also an impact in limiting photosynthesis.

5.2. Photosynthesis limitations within complex canopies

19

As mentioned in Section 3, gm is highly determined by leaf structure, as suggested by the

negative relationship between gm and leaf mass per unit area. Additionally, gm scales positively

with leaf photosynthetic capacity. However, both variables, leaf mass per unit area and

photosynthetic capacity, are positively correlated with local irradiance in canopies, so that opposite

forces operate when increasing height, controlling the gm of leaves. The situation is further

complicated by the fact that in evergreens leaves of different age are found at different tree

heights. Hydraulic limitations in very tall trees exert a limitation on gs especially in the upper

leaves which, in turn, may exert a negative feedback on gm but at the same time older leaves with

expectedly reduced gm might be found at the lower parts of the canopy. As expected, different

results have been obtained when analyzing tree height / leaf canopy position on gm.

For instance, sun leaves at the top of a 34 m tall conifer Pseudotsuga menziesii were

compared with leaves collected at the bottom (10% incident PPFD) [110]. Despite a significant

difference in leaf mass per unit area there was a strong correlation between An and gm. The

variability of gm was high within each irradiance level or leaf type, and the differences in gm

between the locations were not significant. Mesophyll conductance was also studied across the

canopy profile in different-aged leaves of the oak Quercus ilex. Here, in contrast to Pseudotsuga,

strong positive curvilinear relationships between gm and mean irradiance were found for all leaf

age classes except in oldest leaves [111]. However, the degree of limitation of photosynthesis by

gm was actually slightly larger at higher irradiance, suggesting increasing photosynthetic limitation

by gm at the top of the canopy [111]. The spatial distribution of structural (leaf N and chlorophyll

content and leaf mass per unit area), and functional leaf traits (maximum velocity of carboxylation,

maximum capacity for electron transport and gm) were studied along the canopy of the deciduous

Fagus sylvatica in relation to irradiance and leaf age [112]. A multivariate approach was used

based on path analysis to disentangle the relationship among these variables. The primary role of

structural adjustment was confirmed i.e., the plastic response of leaf mass per unit area which was

20

in this case negatively related to gm, for the acclimation of leaves to the local irradiance in a

canopy. In much taller trees, however, hydraulic limitations could exert a larger role than local

irradiance in setting photosynthetic characteristics of the top leaves. For instance the response of

leaf mass per unit area to local irradiance was altered in Sequoia sempervirens (113 m) as height

increased [113]. There was a transition region in the canopy where the primary determinants of

leaf morphology and structure switched from local irradiance to hydraulics. It was concluded that

structural changes due to hydraulics indirectly reduced net CO2 assimilation rates via increased

respiration rates and decreased gs and gm.

The other question is whether total tree height itself (i.e., not the height of a given leaf

inside a tree, but the total height of the tree itself) can alter gm and its role in constraining

photosynthesis. Specifically, leaf mass per unit area increases as trees increase in height and this is

associated with reductions of net CO2 assimilation [114-116], gs [117] and, perhaps, gm [114, 118,

119]. Lower gm in taller trees has recently been confirmed experimentally. There was a decrease of

gm with total tree height in the conifer Pseudotsuga menziesii [120], suggesting that gravity and the

water path length were likely the main determinants of trends in foliar characteristics via their

effects on leaf water potential during leaf expansion. Also, there was a tight relationship between

leaf mass per unit area and gm in Pinus densiflora that was the inevitable consequence of the

morphological acclimation to height [79]. Similarly, the age effect on gm in leaves of the

deciduous Nothofagus solandri was only evident in tall trees (15 m tall), while in shorter trees (2

m tall) no differences were found [81]. It seems that changes in gm with tree height occur in

proportion to changes in gs and photosynthetic capacity, such that photosynthesis is limited to a

similar degree by gm in different-size trees [14, 116].

To sum up, most studies conclude that the main determinant of gm modifications with tree

height is leaf structure represented by leaf mass per unit area, which can be modulated by local

21

irradiance, leaf age and hydraulic gradients. The complexity of their interactions does not allow

yet a clear prediction of gm changes with tree height.

6. Modeling and including gm in photosynthesis models

Mesophyll diffusion of CO2 must be taken into account in leaf gas exchange models, since

considering an infinite gm is not correct. The difficulty rises when deciding a value of gm to be

applied in each specific scenario, and as a function of how it varies in space and time. Currently,

we are not able to incorporate gm in models with a mechanistic basis due to the lack of sufficient

knowledge on the mechanisms involved in the regulation of gm. This being said, there have been

several attempts to empirically include gm in models. One of the first examples was proposed

modeling the soil-plant-atmosphere continuum in a Quercus-Acer forest [121]. These authors, as

[122], concluded that Vcmax and Jmax were underestimated in most studies due to neglecting gm.

They included a different constant value of gm for each species. Later on, two approaches were

used in rice to include a variable gm as a function of N or as a function of gs [123]. The models

were based on previous work where gm usually scaled with gs. The model based on gs explained

more variation in measured An than the model based on N. It was argued that gm changes during

different developmental stages of the crop, and the apparent coordination between gm and gs

allowed the use of gs as a scaling factor. The same approach was used in modeling the response of

C3 and C4 plants to water stress [124]. The inclusion of gm in a photosynthesis model was further

justified by the response of gm to temperature [11]. None of these approaches allows for a flexible

dependency between gm, gs and photosynthetic capacity like the one that occurs, for instance,

under water stress.

One of the remaining challenges in leaf gas exchange models is to take into account the

effects of seasonal water stress. Water stress, as mentioned above, affects the relative importance

of each component in limiting photosynthesis, depending on the degree of stress. In this sense,

22

some have used a limitation analysis [43] to infer what must be included in the models that mimic

the observed behavior of An. Three values of gm were used to simulate An assuming that stomatal

limitation is equal, smaller or larger than mesophyll limitation [125]. It was concluded that

diffusive limitations can explain water flux responses to seasonal changes in soil water availability

only if gm was included in the models. The use of either stomatal or biochemical limitation alone

did not mimic the observed data. The same conclusion was reached about the importance of

combining several components in the limitation during acclimation to stress [108]. They concluded

that to reproduce the general pattern of C3 photosynthesis during water stress, the highest

limitation strength must be imposed by gm, then by gs, and finally by the biochemical capacity.

The impact of gm on model predictions of carbon isotope discrimination has been also

assessed by testing whether a fixed or a variable gm depending on gs or time of day improved

model predictions in mature juniper trees [126]. The incorporation of gm in the model did not

consistently improve carbon isotope discrimination. These results contrast with those were the

inclusion of a variable gm (as a function of gs), improved the model predictions of isotope

composition of respired carbon from a coastal Douglas-fir forest in comparison with a model with

a fixed gm [124]. Recently, [127] have warned about the need of including the ternary effect of

transpiration rate in the equations for carbon isotope discrimination. The effect is greatest when the

leaf-to-air vapor mole fraction difference is greatest, which could explain some of the

contradictory results commented above.

Although it is obvious that a realistic model for predicting An should incorporate gm, Oliver

et al. [128] concluded that the use of gm did not improved the performance of the An model, as long

as Vcmax was seasonally tuned. Effectively, a similar prediction of An can be obtained either

reducing gm or overreducing Vcmax, i.e., Cc or Ci-basis. However, if we are interested in using a

mechanistic model, the actual regulation of gm and Vcmax as a function of the degree of stress

should be taken into account. In this sense, Niinemets et al. [14] showed how the inclusion of gm in

23

models results in a description of leaf acclimation to changing environmental conditions, and in a

more realistic description of daily photosynthesis, especially in leaves under stress. While An-Ci

parameterization predicted a negative carbon balance at midday in plants under water stress, actual

measurements and simulations with the An-Cc approach yielded a carbon gain. Similarly, a

biochemical photosynthesis model on a Cc-basis was used to explain the potentially favorable

response of evergreens plants to climate change due to their robust leaves and low gm [15].

Currently, the determination of the seasonal evolution of gm or its dynamic in cycles of stress and

recovery, and even distribution within canopies, is seen as a huge drawback in the process of

incorporation in models of process-based land-surface schemes [128]. Definitely, more

information is needed to make possible the inclusion of gm in leaf-gas exchange models. This

information is hard to be obtained at a large scale of space and time due to the limitations in the

use of most used techniques of gm determination [10]. However, more efficient and

straightforward methods for determining average canopy gm, like that proposed by Ubierna and

Marshall [129] based on δ13C of phloem content, can be useful in the future for ecophysiological

and ecosystem model applications.

7. Can mesophyll conductance be uncoupled from the water path regulation? 7.1. Co-regulation of gm and stomatal conductance

The previous sections have demonstrated that gm and gs are very often co-regulated,

although not under all instances. Some degree of co-regulation has been suggested between gm and

plant hydraulics. Water vapor and CO2 share at least a part of their pathways in leaves. Both gases

are exchanged with the atmosphere through stomata. In addition, both water vapor and CO2 must

cross the aerial sub-stomatal cavity. Additionally, after leaving the leaf xylem, liquid water not

only moves along apoplastic pathways but also (partly mediated by aquaporins) crosses cell

membranes and flows through the plasmalemma (symplastic pathway) and cell vacuoles

24

(transcellular pathway) to the sites of evaporation [130, 131]. Accordingly, liquid water and CO2

diffusion share partly common diffusion pathways in the mesophyll [13, 16]. The involvement of

aquaporins in the diffusion of water and possibly CO2 also suggests at least partly common

pathways for both molecules, although it is also possible that different aquaporins could be

involved in each case.

Because of overlapping transport pathways, some degree of co-regulation is expected

between gm and water transport in leaves. Indeed, variations of gm are generally closely related to

those in gs, e.g., variations among species (see Section 2), induced by water stress (see Section 4),

etc, but not necessarily in transgenic plants with different levels of aquaporins (see Section 3) or

under combined water stress and low irradiance (see Section 4). From a purely photosynthetic

perspective, this co-regulation is expected and may optimize photosynthesis. For instance, energy

and water-consuming stomatal opening does not translate into effective photosynthesis if gm equals

zero, but requires higher gm.

However, from the perspective of leaf water use efficiency, theoretical considerations

suggest that some uncoupling between the two conductances may be advantageous. Under steady-

state, net photosynthesis is:

An = gs (Ca – Ci) = gm (Ci – Cc),

where Ca, Ci and Cc are the atmospheric, sub-stomatal and chloroplastic CO2

concentrations, respectively. An /gs is of the intrinsic water use efficiency at the leaf level, as gs

controls transpiration in a constant environment. From the equation, at constant photosynthetic

activity (i.e., ‘demand’ for Cc), increased An/gs can be achieved by increasing the ratio of gm to gs.

Some degree of uncoupling between the two conductances, i.e. variation in gm/gs has been

observed. There is a progressive increase in gm along the leaf of the monocot Triticale, but little

variation in gs [132]. In this case, gm is the main driver for changes in observed carbon isotope

discrimination (∆13C), an indicator of Cc / Ca. Dry climate populations of the deciduous trees Picea

25

[133] and Populus [134] have larger gm/gs than their relatives from milder climates. Genetic- and

drought-induced variability in gm/gs in grapes [135] and tomato [136] is significantly and

positively correlated with water use efficiency. In all these examples, increased gm/gs and water

use efficiency was accompanied by decreased An, suggesting that manipulating water use

efficiency by means of gm regulation may always result in decreased production capacity.

However, a simultaneously higher An, gm/gs and water use efficiency was observed in the

evergreen conifer Abies pinsapo than in its close relative A. alba (Peguero-Pina, unpublished).

Similarly, a close relationship was found between An and gm along a range of Pseudotsuga

menziesii trees varying in total height, but virtually no change in gs i.e., a higher gm/gs as total

height declined and An and water use efficiency increased [80]. Understanding the mechanisms

regulating gm in such a way that it can uncouple from gs to some extent may be an essential step

for future genetic manipulation of plants aiming simultaneous increases in photosynthesis and

water use efficiency.

7.2. Co-regulation of gm and hydraulic conductance in the mesophyll

At least in part, tight co-regulation of gm and gs may arise from the close relationship often

found between gs and the conductance of water within the mesophyll. Up to now, it has not been

possible to determine hydraulic conductance of the mesophyll directly, but several methods to

measure whole leaf hydraulic conductance (Kleaf) are available, mainly based on the measurement

of water flow relative to a water potential gradient[137]. A general positive relationship occurs

across species between gm and Kleaf, with fast growing species showing the highest values for both

variables and conifers falling in a group with the lowest values (Fig. 7a). The underlying reason

for such relationship might be the existence of anatomical limitations to CO2 and water

conductances, which are likely to be higher in species with thicker mesophyll layers and greater

surface of mesophyll cells [80, 138-142]. Nevertheless, this does not seem to be a universal

26

relationship, and herbaceous monocots with high gm, around 0.5 mol m-2 s-1 [36, 132, 143], may

have Kleaf values below 5 mmol H2O s-1 MPa-1 m-2 [144, 145]. Whether this is due to anatomical or

biochemical particularities of these species is still a matter of debate. In this sense, at least for

some species the pattern of change in response to drought and tree height for gm and Kleaf is

comparable to the general pattern observed across species (Fig. 7b), suggesting that not only

anatomical but also differences in biochemical regulation are involved in interspecific differences

for both variables.

The main limitation of Kleaf as a surrogate for the hydraulic conductance of the mesophyll

is that Kleaf involves both mesophyll and xylem resistances, and although the former plays a

significant role in whole Kleaf, its relative contribution may vary with species and experimental

conditions [130, 137, 146, 147]. Studies on the environmental response of leaf water isotopic

enrichment offer a new way to assess short-term changes in mesophyll hydraulic resistance [148-

151]. During transpiration, leaf water becomes enriched in the heavier isotopes, 18O and 2H. The

enrichment at the sites of evaporation can be modeled from environmental variables [152, 153].

(see Appendix I for details). However, the observed enrichment in the leaf lamina does not

generally agree with modeled values at the site of evaporation, since back diffusion of enriched

water from the sites of evaporation to the rest of the leaf is counteracted by a mass flow of non-

enriched water driven by transpiration (Péclet effect [154]). The magnitude of this effect is

proportional to the transpiration rate, the distance from the xylem to the evaporative surface, and a

scaling factor, which accounts for the higher velocity of water through a porous media than if it

were moving through the leaf as a slab (i.e. as derived from transpiration). From these models, a

“scaled effective path length” (Leff, the product of the actual distance and the scaling factor) can be

determined by comparing modeled enrichment at the site of evaporation with observed values

[154-156]. Since Leff accounts both for the length of the water pathway and its tortuosity, it is

theoretically related to mesophyll hydraulic resistance to water flow. In a recent work, Ferrio et al.

27

[149] showed a tight link between Leff and both Kleaf and gm in response to experimental treatments

(Fig. 8), although the relationship between Leff and gm reached an asymptote at higher values of gm

(gm >200 mmol CO2 m-2 s-1; Fig. 8b). These findings provided empirical evidence in support of the

theoretical link between Leff and hydraulic conductance of the mesophyll. Most interestingly, they

also showed that at least in response to certain environmental variables, changes in gm and

hydraulic conductance of the mesophyll are closely and positively related, implying that the gm / gs

ratio can vary but over a limited range. Nevertheless, the lack of relationship between gm and Leff

at higher values of gm suggests that diffusion of CO2 can be enhanced beyond the common

limitations for water and CO2. It is likely, for example, that well-watered plants may have reached

their maximum values of hydraulic conductance of the mesophyll, determined by anatomical

limitations, while gm may still respond to other regulations that maximize photosynthesis. One

possible explanation for the uncoupling between CO2 and water conductances has been proposed

[51]: the aquaporin NtAQP1, from the PIP1 family, did not increase water transfer, but enhanced

CO2 diffusion. Conversely, NtPIP2;1 from the PIP2 family, favored water transport but did not

affect CO2 diffusion. The changing of the proportion of the two different aquaporins in a tetramer

progressively varied the water and CO2-related functions. As a consequence, even though both leaf

hydraulics and CO2 diffusion respond to changes in aquaporin conductivity, different

combinations of aquaporin subunits in aquaporin tetramers may promote either water or CO2

transfer, or both, depending on the proportion of PIP1 or PIP2. Thus, regulation of the function of

aquaporins would take place as a result of a competition among subunits for the formation of

tetramers, in a way that would allow enhancing CO2 fixation and at the same time reducing water

use. Indirect evidence in vivo in support to this hypothesis was obtained by comparing the values

of gm and effective path length in a wild type and two tobacco mutants and antisense and

overexpressing NtAQP1lines (Fig. 9) (Kodama, unpublished, plants courtesy of Dr. R.

Kaldenhoff). Plants with increased gm had increased effective path length (i.e., decreased hydraulic

28

conductance of the mesophyll). The overexpressing line (with a greater expression of PIP1s) had

the highest gm and effective path length, and the antisense line had the lowest values. We speculate

that this is the result of different aquaporin forms proportion in tetramers following altered

expression of one of the two forms (PIP1 and PIP2). According to [51], one water conducting

aquaporin (PIP2) is enough to facilitate water transport to a level close to maximum, while 3 or 4

CO2 conducting aquaporins (PIP1) are required to reach maximum CO2 diffusion. We suggest that,

in antisense lines, the proportion of PIP1 aquaporin in most aquaporin tetramers falls well below 3,

while in overexpressing lines the proportion is between 3 and 4. In contrast, the effective path

length and gm were negatively correlated when comparing individual plants within each mutant

type, suggesting a common trend for CO2 and water conductance. In this case, we suggest that

variations in the total expression of aquaporins among individuals, while keeping identical

proportions among subunits, results in a concomitant increase in conductance of CO2 and of water

vapor.

8. Concluding remarks and future prospects

We have stressed that the share of overall photosynthetic limitation by mesophyll

conductance is large and can be the most significant factor limiting photosynthesis under certain

conditions and certain plant functional types. This statement is backed up by ample evidence, and

we argue that gm should be included in any study analyzing limitations to photosynthesis, as well

as in models for predicting rates of photosynthesis.

Significant progress has recently been made in quantitatively linking gm to foliage

anatomical and structural traits. Cell wall thickness and chloroplast distribution seem to play a

dominant role in determining the upper limit of gm. However, rapid variations in response to

environmental cues might not be regulated by anatomical traits. Aquaporins seem to be only partly

responsible, although their mechanistic bases remain unclear.

29

We conclude that further developments in the field require more advanced understanding

of the currently most obscure points, which include:

1. The role of aquaporins in diffusion conductance, especially in species growing in

stressful environments and having particularly low values of gm.

2. To what extent water and CO2 transport processes are coordinated and how does this

affect photosynthesis? It seems that the coordination is not necessarily maintained across

environmental gradients and gradients of tree height.

3. What is the genetic basis of gm and its genetic variability? Data on genetic variability

within species, the degree of heritability of gm, as well as for entire phylogenetic groups, notably

ferns and mosses are far too scarce.

Acknowledgements

We thank Ichiro Terashima and Yusuke Mizokami for insightful suggestions on the MS

and editor plus five additional anonymous reviewers for numerous useful improvements. The

study was financially supported by the Estonian Ministry of Science and Education (grant

SF1090065s07), the Spanish Ministry of Science and Innovation through projects BFU2008-

01072 (MEFORE), AGL2009-11310/AGR, BFU2011-23294 (MECOME) and CGL2009-13079-

C02-01 (PALEOISOTREE), and the European Commission through European Regional Fund (the

Estonian Center of Excellence in Environmental Adaptation), and the Marie Curie project MC-

ERG-246725 (FP7). J.P.F. is supported by the Ramón y Cajal program (RYC-2008-02050). A.G.

had a Swiss National Science Fellowship (PA00P3_126259). M.M.B. is supported by an

Australian Research Council Future Fellowship (FT0992063). CD was supported by a grant from

the French government and by the cooperation project Tranzfor (Transferring Research between

EU and Australia–New Zealand on Forestry and Climate Change, PIRSES-GA-2008-230793)

funded by the European Union.

30

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40

Figure legends Figure 1. Mesophyll conductance is greatest the more a species is phylogenetically evolved. Average ± S.E. values for gs and gm in different pooled groups of plants. Data from liverworts and hornworts from [17], data for all other groups from [41]. Figure 2. Mesophyll conductance reflects the CO2 diffusion pathway, which is composed of air, water and lipid barriers. Comparison of CO2 diffusion pathway within the fully expanded needle of evergreen conifer Abies alba (a-c) and within the leaf of broad-leaved deciduous Populus tremula (d-f) according to light (a, b, d), scanning (c) and transmission electron (e, f) micrographs. Leaf cross-sections (a, d) illustrate the CO2 gas phase diffusion pathway from ambient air (Ca) to sub-stomatal cavities (Ci) and from sub-stomatal cavities to outer surface of cell walls, Ci,w. The CO2 concentration drawdown, Ca-Ci, depends on stomatal conductance, while the drawdown Ci-Ci,w is characterized by internal gas-phase diffusion conductance (gias) that is determined by effective mesophyll thickness and porosity. The micrographs of palisade tissue (b, e) demonstrate parallel diffusion pathways within cells (indicated with arrows for representative cells) that is determined by the exposure of chloroplasts to intercellular airspace. The representative micrographs of palisade cells (c, f) illustrate CO2 diffusion pathways in liquid phase from mesophyll cell outer surface to chloroplasts. The CO2 drawdown from outer surface of cell walls to chloroplasts (Cc, Ci,w-Cc) is determined by liquid-phase diffusion conductance gliq that consists of cell wall (cw), plasma membrane (pm, not visible in the micrographs), cytoplasm (cyt), chloroplast envelope (env, not visible in the micrographs), and chloroplast stroma (chl). Micrographs from Peguero-Pina et al. [62] (a-c) and Tosens et al. [15] (d-f), with permission. Figure 3. Altered expression of aquaporins in relation to mesophyll conductance limitations of photosynthesis. Average (error bars show +SE) net assimilation rate, stomatal conductance to CO2 and mesophyll diffusion conductance (upper panels) and relative photosynthetic limitation due to limited biochemical capacity, stomatal conductance and mesophyll diffusion conductance (lower panels) in transformed plants with reduced (AS, RNA-interference) and over-expressed (OE) aquaporins and corresponding controls (either wild type or plants transformed with the same construct used for AS and OE, but lacking the modified aquaporin expression phenotype). As the data represent one-to-one correspondence between data pairs (control vs. AS and control vs. OE and AS vs. OE within the given study), the averages between the treatments and corresponding controls and between AS and OE were compared by paired t-tests that is a more powerful statistical test than standard ANOVA [141]. Statistical significance as: ns – not significant, * - P<0.05, ** - P < 0.01, *** - P < 0.001. The data are for Arabidopsis thaliana aquaporins atpip1;2-1 and atpip2;3-1 [32], Nicotiana tabacum aquaporin NtAQP1 [33-35] and Hordeum vulgare aquaporin HvPIP2;1 [36]. The data correspond to saturating light, leaf temperature of 25 °C and chamber CO2 concentration of 280-400 µmol mol-1. The relative limitations of photosynthesis were calculated according to [43] and the three imitations sum up to 1. Maximum carboxylase activity of Rubisco, Vcmax, needed for these calculations was determined by inverse modeling as in [44]. Means between treatment and corresponding controls and between AS and OE were compared by paired t-tests (ns – not significant, * - P<0.05, ** - P < 0.01, *** - P < 0.001). Figure 4. Co-regulation of stomatal conductance, mesophyll conductance and photosynthesis in wild type and mutants with altered expression of aquaporins. Net assimilation rate (An) in relation to (a) stomatal conductance to CO2 (gs) and (b) mesophyll diffusion conductance (gm), and correlations between (c) the CO2 drawdown due to limited gs (difference of CO2 concentrations in ambient air and sub-stomatal cavities, Ca-Ci=An/gs) and (d) the CO2 drawdown due to limited gm

41

(difference in CO2 concentrations in sub-stomatal cavities and chloroplasts, Ci-Cc = An/gm). Every data point corresponds to an average value of either control, aquaporin overexpressed, aquaporin antisense or aquaporin-inhibited plants reported in original studies. Data sources for transformed plants as in Fig. 3. Data for HgCl2 treated (0.3-1.2 mM) and non-treated control plants were from [39] (Vicia faba) and [37, 38] (Nicotiana tabacum). Environmental conditions during measurements as in Fig. 3. The number of data points in different panels differs because not all studies reported the whole suite of characteristics An, gs, gm, Ci and Cc. Figure 5. Increasing CO2 concentration reduces mesophyll conductance. gm correlates with Ci over a broad range of ambient CO2 concentrations and across a number of different species and growth forms. The isotopic method (δ13C) and the combined chl fluorescence and infrared gas exchange analysis method are shown in closed and open circles, respectively. Data are taken or calculated from [86], [88], [157], [89], [99], [96], [90], [91], [97], [158], [87], [92], [93], [94], [11]. Figure 6. Mesophyll conductance limitations increase as photosynthesis declines (total limitation increase) in response to stress. Empty circles represent stomatal limitation (SCL), filled circles mesophyll conductance limitation (MCL) and triangles biochemical limitation (BL). Data have been compiled from the following references: [83] , [124], [102], [108], [66, 90], [67, 71], [101], [159], [160], [104], [107], [105], [84], [81] and [109].

Figure 7. Mesophyll conductance co-regulated with hydraulic conductance. A) Strong relationship between average leaf hydraulic conductance (Kleaf) and mesophyll diffusion conductance (gm) for different plant species, based on literature data (see Supplemental Information for the list of references). B) Comparative response of different species to changes in growing conditions affecting both gm and Kleaf: high/low water stress for Quercus, Fagus and Pinus; canopy height for Pseudotsuga; a combination of drought and vein severing for Vitis.

Figure 8. Mesophyll conductance and hydraulic conductance co-regulate with the effective pathlength of mesophyll water movement. Strong relationship between treatment averages for leaf lamina hydraulic conductance (Klamina), scaled effective pathlength (Leff) and mesophyll conductance for CO2 (gm) in Grenache grape. Treatment averages for gm were calculated excluding values above 200 mmol CO2 m

-2 s-1, which were beyond the linear range for the relationship between gm and Leff (see inset with individual leaf values). Circles: control plants, triangles: drought plants. Open symbols: intact leaves. Closed symbols: vein-severed leaves. Data from [149]. Figure 9. Altered expression of PIP 1 aquaporins results in co-variations of the mesophyll conductance and the effective pathlength of mesophyll water transfer. Upper panel: the relationship between gm and the path length of mesophyll water transfer (L) in wild-type (circles), anti-sense (downwards triangles) and over-expressing (up-wards triangles) tobacco plants with altered levels of NtAQP1. Empty dots are individual plants within each genotype, and filled dots average values per genotype. Lower panel: potential explanation for the opposite relationships found between gm and L within and between genotypes, based on the findings by Otto et al. [51]: negative correlations between gm and the path length of mesophyll water transfer occur between genotypes, likely reflecting that altered expression of one aquaporin class results in different proportions of aquaporin classes within tetramers; positive correlations between gm and the path length of mesophyll water transfer occur between individuals within each genotype, likely reflecting different concentrations of aquaporins rather than different proportions of aquaporin classes within tetramers.

42

FIGURE 1

43

FIGURE 2

44

FIGURE 3

45

FIGURE 4

46

FIGURE 5

47

relative TL

0,0 0,2 0,4 0,6 0,8 1,0

rela

tive

SC

L, M

CL,

BL

0,0

0,2

0,4

0,6

0,8

1,0

TL vs MCL TL vs SL TL vs BL

FIGURE 6

48

g m (

mm

ol C

O2

m-2

s-1

)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

Herbs monocotsHerbs dicots Deciduous angiosp. Ev. angiosp. Ev. gymnosp.

gm=0.0268+0.0156*Kleaf

r2=0.659 N=20 P<0.001

Kleaf (mmol H2O s-1 MPa-1 m-2)0 5 10 15 20 25

gm (

mm

ol C

O2

m-2

s-1)

0.0

0.5

1.0

1.5

Kleaf (mmol H2O s-1 MPa-1 m-2)0 5 10 15 20 25

g m (

mm

ol C

O2

m-2

s-1

)

0.0

0.1

0.2

0.3

0.4

QuercusFagusPinusPseudotsugaVitis

gm=-0.0036+0.0206*Kleaf

r2=0.594 N=14 P<0.001

A)

B)

FIGURE 7

49

Klamina (mmol H2O m-2 s-1 MPa-1)2 4 6 8 10

L eff (

mm

)

0

20

40

60

80

100

gm(mmol CO2 m-2 s-1)

0 50 100 150 200

ControlControl-VSDroughtDrought-VS

Leff=91-485*gm

r2=0.979 P=0.011

A) B)

Leff=138-15.9*Klamina

r2=0.991 P=0.005

gm (mmol CO2 m

-2 s-1)0 100 200 300

L eff (

mm

)

0

50

100

150

r2=0.566P<0.001

FIGURE 8

50

AS WT OE

Plant 1 Plant 1 Plant 1

Plant 2 Plant 2 Plant 2

Increasing CO2 transport and declining water transport (high L)

Increasingboth

CO

2and

water

transport

FIGURE 9

Appendix A: Supplementary data Table S1. Average and standard deviation of leaf hydraulic conductance (Kleaf) and mesophyll diffusion conductance (gm) across the different genera included in Fig. 8. The “OUT” column indicates the values not included in the linear regression plotted in Fig. 8a.

Genus Kleaf

(mmol H2O s-1 MPa-1 m-2)

gm

(mmol CO2 m-2 s-1)

OUT References Kleaf References gm

Herbaceous monocots

Triticum 3.1 ±0.00 0.44 ±0.072 X [1],[2],[3] [4],[7],[5],[6],[8] Oryza 7.5 ±3.89 0.56 ±0.410 X [9] [10],[11],[8] Herbaceous dicots

Phaseolus 19.5 ±4.72 0.28 ±0.115 [12],[13] [14],[15],[16],[17],[18],[8],[19] Helianthus 13.2 ±3.31 0.79 ±0.545 X [12],[20],[21] [22],[23],[17],[24],[25] Vicia 15.7 ±0.00 0.40 ±0.060 [26] [6],[27] Glycine 11.2 ±0.00 0.49 ±0.165 X [28] [29],[30],[31] Arabidopsis 11.5 ±1.90 0.20 ±0.000 [32] [33],[34] Nicotiana 26.0 ±4.00 0.30 ±0.205 X [35] [36],[37],[33],[30],[38],[39],[31],[40],[41],[42],[8]Gossypium 12.2 ±1.10 1.06 ±0.745 X [28],[43] [22],[44] Woody deciduous angiosperms

Quercus 7.5 ±1.71 0.14 ±0.032 [45],[46],[48],[20],[47] [31],[49],[6],[50],[51],[52],[53],[54] Fagus 7.1 ±0.46 0.16 ±0.094 [46] [55],[19] _Acer 7.4 ±1.35 0.05 ±0.011 [56],[20] [58],[17],[57],[50] alnus 7.9 ±0.00 0.12 ±0.017 [59] [17],[57],[50] populus 10.6 ±2.20 0.22 ±0.059 [45] [60],[17],[57],[50],[51],[61],[52],[18] betula 11.0 ±3.00 0.77 ±0.335 X [47],[62] [63],[64],[65],[66] Tilia 7.0 ±0.10 0.92 ±0.415 X [45] [65],[24] Juglans 8.0 ±3.00 0.15 ±0.035 [67] Corylus 7.8 ±0.56 0.18 ±0.000 [20] [50] Castanea 4.4 ±0.83 0.11 ±0.000 [20] [22],[55],[68] Vitis 11.0 ±2.18 0.16 ±0.044 [1],[47] [69],[1],[70],[71],[15],[33],[72] Woody evergreen angiosperms

Quercus 3.0 ±1.44 0.08 ±0.013 [20] [73],[17],[74],[6],[75],[76],[52] Olea 8.9 ±0.28 0.22 ±0.135 [20] [77],[78],[79],[33],[80],[75] Camellia 6.0 ±0.00 0.10 ±0.025 [21] [17],[74] Hedera 10.4 ±0.26 0.15 ±0.000 [47] [6] eucalyptus 9.9 ±0.42 0.15 ±0.014 [81] [82],[83] [49],[6],[8],[84],[85],[86] Laurus 2.2 ±0.56 0.08 ±0.000 [20] [75] Woody evergreen gymnosperms

Pinus 5.3 ±1.12 0.13 ±0.020 [87],[48],[88] [14],[50],[89] Pseudotsuga 5.1 ±0.67 0.11 ±0.087 [48],[90] [14],[91],[50],[92],[90]

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Appendix B Leaf water enrichment models and scaled effective path length

Steady-state isotopic enrichment over source water at the site of evaporation (e) has been described by the Craig & Gordon model [1-2]:

e k v k ea

ei

(Eq. S1)

where + is the equilibrium fractionation between liquid water and vapour [3]; k is the kinetic fractionation as vapour diffuses from leaf intercellular spaces to the atmosphere [4-5], v is the isotopic enrichment of atmospheric water vapour relative to plant source water, and ea/ei is the ratio of ambient to intercellular vapour pressures.

The steady-state isotopic enrichment of mean lamina mesophyll water (LsP) can be described by the above steady-state Craig & Gordon model corrected for the gradient from xylem source water to enriched water at the evaporating sites, the so-called Péclet effect [6]:

LsP e

1 e

with

D

lv (Eq. S2)

where (Péclet number) is the ratio of convection to diffusion, v is the linear velocity of water movement (m s-1), l is the length of the water pathway along which diffusion occurs (i.e. the distance between the xylem and the evaporation surface), and D the tracer-diffusivity (m2 s-1) of heavy water isotopologues (either H2

18O or 2H1HO) in ‘normal’ water. Linear velocity through the water pathway (v) can be related to transpiration rate (E, mol H2O m-2 s-

1) as follows [7]:

C

Ekv (Eq. S3)

where C is the molar concentration of water (55.56 103 mol m-3) and k is a scaling factor to convert the velocity of water moving through the leaf as a slab (E/C) to the actual velocity in a porous medium, and usually ranges from 102 to 103. Accordingly, can be also expressed as:

DC

LE

eff (Eq. S4)

where Leff stands for the scaled effective pathlength, i.e. the product of l and k. Thus, Leff is expected to be much larger than the actual distance between the xylem and the evaporation sites, and would vary not only with changes in l but also with changes in the tortuosity of the water pathway (e.g. varying the proportion of apoplastic and cell-to-cell water pathways; [8]).

References Appendix B

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